Time-Inconsistent Planning: A Computational Problem in Behavioral Economics

TL;DR

This paper introduces a graph-theoretic model to analyze time-inconsistent behavior in decision-making, capturing phenomena like procrastination and abandonment, and explores task design strategies to motivate goal achievement.

Contribution

It presents a novel graph-based framework for modeling time-inconsistent planning and analyzes its properties, including the limited variety of behaviors and structural causes of increased costs.

Findings

Polynomially many distinct behaviors in any graph.

Large procrastination structures lead to higher costs.

Task design can influence agent motivation.

Abstract

In many settings, people exhibit behavior that is inconsistent across time --- we allocate a block of time to get work done and then procrastinate, or put effort into a project and then later fail to complete it. An active line of research in behavioral economics and related fields has developed and analyzed models for this type of time-inconsistent behavior. Here we propose a graph-theoretic model of tasks and goals, in which dependencies among actions are represented by a directed graph, and a time-inconsistent agent constructs a path through this graph. We first show how instances of this path-finding problem on different input graphs can reconstruct a wide range of qualitative phenomena observed in the literature on time-inconsistency, including procrastination, abandonment of long-range tasks, and the benefits of reduced sets of choices. We then explore a set of analyses that quantify over the set of all graphs; among other results, we find that in any graph, there can be only polynomially many distinct forms of time-inconsistent behavior; and any graph in which a time-inconsistent agent incurs significantly more cost than an optimal agent must contain a large "procrastination" structure as a minor. Finally, we use this graph-theoretic model to explore ways in which tasks can be designed to help motivate agents to reach designated goals.